Potential Mechanisms Connecting Purine Metabolism and Cancer Therapy

Yin, Jie; Ren, Wenkai; Huang, Xingguo; Deng, Jinping; Li, Tiejun; Yin, Yulong

doi:10.3389/fimmu.2018.01697

Cited by 313 publications

(255 citation statements)

References 108 publications

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“…The in-silico pKa values are in remarkably close agreement with the experimental pKa values 6.8±0.1 and 9.7±0.1 20 .log => = log =>(1 In equation-(2), y is the kinetic parameter ( 9-? ) for experimental pH-activity curve while y is the conditional probability of CCPS for the in-silico pH-activity curve.…”

supporting

confidence: 79%

“…Hence, we have titrated only the amino-group, not the phosphate group. To titrate the GAR ligand, we have computed the restrained electrostatic potential (RESP) charges 53,54 in both protonated and deprotonated states (Table S1) and the reference energy ( 0809,/01 ) as defined in equation- (1).…”

Section: Methodsmentioning

confidence: 99%

“…To compute the reference energy ( 0809,/01 ), we have titrated the GAR ligand at its experimentally obtained pKa value 63 which nullifies the first term on the right-hand side in equation- (1). We have calculated the second term 0809 in equation-(1) using the RESP charges of the GAR ligand in both protonation states.…”

Section: Parameterization Of the Gar Ligandmentioning

confidence: 99%

“…Cancer refers to a collection of similar diseases which occurs through the process of uncontrolled cell division. Cell division requires purines through the de novo purine biosynthesis and salvage pathways 1,2 . In normal cells, purines are mainly supplied through the salvage pathway 2 ; however, in some cancer cell lines, purines are mainly supplied by the de novo purine biosynthesis pathway 3,4 .…”

Section: Introductionmentioning

confidence: 99%

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Rationalizing the pH-Activity Response for Escherichia Coli’s Glycinamide Ribonucleotidetransformylase Through Computational Methods

Roitberg¹,

Gupta²

2019

Preprint

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<div>Human Glycinamide ribonucleotide transformylase (GAR Tfase), a regulatory enzyme in the de novo purine biosynthesis pathway, has been established as an anti-cancer target. GAR Tfase catalyzes the formyl transfer reaction from the folate cofactor to the GAR ligand. In the present work, we study E. coli GAR Tfase, which has high sequence similarity with the human GAR Tfase with most functional residues conserved. E. coli GAR Tfase exhibits structural changes and the binding of ligands that varies with pH which leads to change the rate of the formyl transfer reaction in a pH-dependent manner. Thus, the inclusion of pH becomes essential for the study of its catalytic mechanism. Experimentally, the pH-dependence of the kinetic parameter kcat is measured to evaluate the pH-range of enzymatic activity. However, insufficient information about residues governing the pH-effects on the catalytic activity leads to ambiguous assignments of the general acid and base catalysts and consequently its catalytic mechanism. In the present work, we use pH-replica exchange molecular dynamics (pH-REMD) simulations to study the effects of pH on E. coli GAR Tfase enzyme. We identify the titratable residues governing the pH-dependent conformational changes in the system. Furthermore, we filter out the protonation states which are essential in maintaining the structural integrity, keeping the ligands bound and assisting the catalysis. We reproduce the experimental pH-activity curve by computing the population of key protonation states. Moreover, we provide a detailed description of residues governing the acidic and basic limbs of the pH-activity curve.</div>

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supporting

confidence: 79%

Section: Methodsmentioning

confidence: 99%

Section: Parameterization Of the Gar Ligandmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Rationalizing the pH-Activity Response for Escherichia Coli’s Glycinamide Ribonucleotidetransformylase Through Computational Methods

Roitberg¹,

Gupta²

2019

Preprint

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“…Gene function (GO biological process and KEGG pathways) annotation revealed that the two bad survival lncRNAs (FIRRE and LINC00839) of the four‐lncRNA signature are involved in the processes, which promote cancer progression such as telomere maintenance, DNA replication, and DNA repair. It seems that metabolism processes also play an important role in NB since the function prediction identified many metabolism processes such as purine metabolism, tRNA metabolic process, nucleotide metabolic process, cysteine, methionine metabolism, etc In fact, purines are basic components of nucleotides in cell proliferation, thus, impaired purine metabolism is associated with the progression of cancer 44 . However, how does purine metabolism affect NB progression or regression is unknown.…”

Section: Discussionmentioning

confidence: 99%

Identification of prognostic long noncoding RNAs associated with spontaneous regression of neuroblastoma

et al. 2020

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Background:The association between long noncoding RNAs (lncRNAs) and spontaneous regression of neuroblastoma (NB) has rarely been investigated and remains unknown. Objective: To identify prognostic lncRNAs involved in the spontaneous regression of NB. Methods: Differential expression analyses were performed between those samples with an outcome of death in stage 4 NB group and those samples with an outcome of survival in stage 4S NB group in two independent public datasets, respectively.Univariate Cox proportional hazard regression survival analysis was performed in each of the entire cohort to identify those lncRNAs significantly associated with overall survival (OS). Those lncRNAs independently associated with OS were then identified by multivariate Cox survival analysis and used to construct an lncRNA risk score. Results: A total of 20 differentially expressed and survival-related lncRNAs were identified sharing between the two independent cohorts. The expression of each of these 20 lncRNAs was significantly correlated with the expression of NTRK1, which is a wellknown factor involved in NB spontaneous regression. Four lncRNAs (LNC00839, FIRRE, LOC283177, and LOC101928100) were identified to be significantly associated with survival independent with each other and a four-lncRNA signature risk score was constructed. Patients with high lncRNA signature risk score had a significantly poorer OS and event-free survival than those with low lncRNA signature risk score. The four-lncRNA signature has a good performance in predicting survival independent with MYCN amplification (nonamplified vs amplified), age status (<18 months vs ≥18 months), risk status (low risk vs high risk), and International Neuroblastoma Staging System (INSS) stage (INSS 1/2/3/4S vs INSS 4). Conclusions: We identified 20 survival-related lncRNAs that might be associated with the spontaneous regression of NB and developed a four-lncRNA signature risk score. The four-lncRNA signature is an independent prognostic factor for survival of NB patients. | 3801 MENG Et al.

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Overexpression of HPRT1 is associated with poor prognosis in head and neck squamous cell carcinoma

et al. 2021

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Potential Mechanisms Connecting Purine Metabolism and Cancer Therapy

Cited by 313 publications

References 108 publications

Rationalizing the pH-Activity Response for Escherichia Coli’s Glycinamide Ribonucleotidetransformylase Through Computational Methods

Rationalizing the pH-Activity Response for Escherichia Coli’s Glycinamide Ribonucleotidetransformylase Through Computational Methods

Identification of prognostic long noncoding RNAs associated with spontaneous regression of neuroblastoma

Overexpression of HPRT1 is associated with poor prognosis in head and neck squamous cell carcinoma

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